@article{LI2025, 
author = {Weibo LI and Feng GAO and Peng XIAO and Kangzheng HUANG and Daojie RUAN and Junzhuo GAO},
title = {Fault diagnosis of ship diesel power distribution system based on WOA-RF algorithm},
year = {2025},
journal = {Chinese Journal of Ship Research},
volume = {20},
number = {2},
pages = {77-88},
keywords = {fault diagnosis, feature extraction, random forest (RF), failure analysis, whale optimization algorithm (WOA), marine diesel power distribution system, Simulink model},
url = {https://www.sciopen.com/article/10.19693/j.issn.1673-3185.04193},
doi = {10.19693/j.issn.1673-3185.04193},
abstract = {ObjectiveThe marine diesel generator (DG) power distribution system is crucial for ship navigation. However, due to the harsh marine environment, frequent failures occur. Therefore, a fault diagnosis method based on whale optimization algorithm-optimized random forest (WOA-RF) is proposed for the marine DG power distribution system.MethodsThe marine DG power distribution system model is built using Matlab/Simulink simulation software. First, fault and normal condition data are collected. Then, the collected data is normalized, time-domain features are extracted, and important features are selected using random forest to reduce data dimensionality. Finally, the WOA-optimized random forest model is used for fault identification, diagnosis and classification.ResultsSimulation results show that the WOA-RF method can identify fault and normal states with 100% accuracy. It can classify 12 different fault types with an accuracy of 98.26%. In the original dataset, the accuracy of WOA-RF improved by at least 4.86% and by up to 34.37% compared to nine different algorithms. In the dataset with 10 dB noise, the accuracy of WOA-RF improved by at least 2.43% and by up to 18.40% compared to six different algorithms.ConclusionThe WOA-RF-based fault diagnosis method demonstrates superior accuracy and robustness in complex marine environments, providing a reliable solution for fault identification in marine power systems.}
}